Energy storage system data dynamic threshold inflection point detection method and detection system

Abstract

The invention relates to the technical field of battery detection, in particular to an energy storage system data dynamic threshold inflection point detection method and system, and the method comprises the steps: collecting and processing battery data, and obtaining battery parameters; the battery parameters comprise battery temperature, charging and discharging current, voltage and electric quantity; based on the charging and discharging current, voltage or electric quantity, acquiring a charging and discharging curve slope change rate of each data point; judging whether the slope change rate of the charging and discharging curve of each data point meets a first preset condition or not; if yes, judging that the data point is an inflection point, and storing information related to the inflection point as inflection point attribute information; judging whether the inflection point attribute information is high-value inflection point attribute information or not; and if yes, storing the inflection point attribute information as target inflection point attribute information. According to the method, the inflection points are accurately recognized by collecting battery data in real time and calculating the slope change rate of the charging and discharging curve, high-value inflection point attribute information is screened and stored, the data storage amount is remarkably reduced, and hardware resources are saved.

Description

Technical Field

[0001] The present invention relates to the technical field of battery detection, and in particular to a method and system for detecting a dynamic threshold inflection point of energy storage system data. Background Art

[0002] In energy storage systems, monitoring the operating status of electrochemical cells, such as lithium-ion batteries, is a key step in ensuring system reliability and safety. Traditional data monitoring methods typically use fixed thresholds or single parameters (such as voltage or current) for inflection point detection. However, these methods have significant limitations: First, they fail to fully consider the impact of battery temperature on electrochemical performance, resulting in the inability to accurately capture the dynamic changes in parameters such as battery internal resistance and electromotive force at different temperature stages. Second, because battery charge and discharge curves exhibit nonlinear characteristics affected by temperature, traditional methods do not consider the use of dynamic thresholds based on battery temperature to detect and identify inflection points. This can lead to excessive inflection point identification or the omission of some important inflection points, resulting in a surge in data storage or information omission.

[0003] In the existing technology, although some solutions have attempted to improve the accuracy of inflection point detection by increasing the sampling frequency or expanding the monitoring parameters, such improvements have instead exacerbated the problem of data redundancy, and no mechanism has been established to associate temperature with the inflection point judgment threshold, resulting in high-value data (such as significant inflection points reflecting the health status of the battery) being submerged in massive amounts of inefficient data. With the large-scale application of energy storage systems, the storage, transmission and processing costs of massive amounts of invalid data have become the core bottleneck restricting the economic efficiency of the system. Therefore, there is an urgent need for a method that can comprehensively consider battery temperature factors and dynamically adjust the inflection point judgment threshold, while accurately identifying high-value inflection points, significantly reducing invalid data storage and achieving efficient use of hardware resources. Summary of the Invention

[0004] The purpose of the present invention is to provide a dynamic threshold inflection point detection method and detection system for energy storage system data in order to solve at least one of the above technical problems. Different dynamic inflection point identification parameters are set for the slope change rate of the voltage, power, and other curves of the battery temperature in the low temperature stage, the medium temperature stage, and the high temperature stage. The threshold value for inflection point discrimination is different at different temperatures, which can more accurately determine the inflection point and retain high-value inflection point information. The present invention can accurately detect data inflection points based on the external characteristics of the energy storage system equipment itself, retain high-value data points, significantly reduce data storage volume, and save hardware resources.

[0005] The present invention achieves the above-mentioned purpose through the following technical solutions:

[0006] A method for detecting a dynamic threshold inflection point of energy storage system data, the method comprising:

[0007] Collect and process battery data to obtain battery parameters; the battery parameters include: battery temperature, charge and discharge current, voltage, and power;

[0008] Based on the charge and discharge current, voltage or power, obtain the rate of change of the charge and discharge curve slope for each data point;

[0009] Determine whether the rate of change of the slope of the charge-discharge curve of each data point meets a first preset condition; if so, determine that the data point is an inflection point, and save information related to the inflection point as inflection point attribute information;

[0010] Determine whether the inflection point attribute information is high-value inflection point attribute information; if so, save the inflection point attribute information as target inflection point attribute information.

[0011] Furthermore, the slope change rate of the charge-discharge curve for each data point is obtained, including:

[0012] Eliminating abnormal data points in the battery parameters;

[0013] Obtain the real-time slope of the charge and discharge curve for each remaining data point;

[0014] The rate of change of the charge-discharge curve slope of each data point is obtained based on the real-time slope of the charge-discharge curve of adjacent data points.

[0015] Furthermore, the abnormal data point is: a data point whose value change in adjacent time domains exceeds a jump threshold;

[0016] The jump threshold is p% of the reference value and is set according to actual needs;

[0017] The reference values ​​include: battery rated voltage and battery rated capacity.

[0018] Furthermore, determining whether the rate of change of the slope of the charge-discharge curve of each data point meets a first preset condition includes:

[0019] The discriminant function g is determined by the inflection point of the energy storage data x (V, Q, t, T, μ x ,…) judge the current data point;

[0020]

[0021] Where V is the battery voltage, Q is the battery charge, t is the time, T is the battery temperature, μ x is the slope of the energy storage charge and discharge curve, “…” is other parameters that characterize the energy storage system, μ x ′ is the slope change rate of the energy storage charge and discharge curve; ε x(T) is the slope change rate threshold; x is a battery parameter associated with the charge and discharge curve; T is the battery temperature;

[0022] When g x (V, Q, t, T, μ x , ...) is 1, it means that the data point is an inflection point that meets the slope change rate threshold; when g x (V, Q, t, T, μ x , ...) is 0, indicating that the data point is not an inflection point that meets the slope change rate threshold;

[0023] |μ x ′|≥ε x (T) indicates that the rate of change of the slope of the charge-discharge curve at this data point meets the first preset condition.

[0024] Furthermore, the slope change rate threshold is:

[0025]

[0026] Among them, ε x (T) is the slope change rate threshold; ε x1 (T) is the first slope change rate threshold; ε x2 (T) is the second slope change rate threshold; ε x3 (T) is the third slope change rate threshold; K1 is the first temperature parameter, K2 is the second temperature parameter, and K1<K2.

[0027] Further, obtaining electrochemical characteristics of the battery based on the material characteristics of the battery, and determining the first temperature parameter and the second temperature parameter based on the electrochemical characteristics of the battery;

[0028] A first slope change rate threshold, a second slope change rate threshold, and a third slope change rate threshold are determined based on material properties of the battery.

[0029] Furthermore, when x=V0, Represents the dynamic threshold value of the voltage inflection point identification parameter during the charging and discharging of the energy storage system; V0 represents the voltage curve during the charging and discharging of the energy storage system;

[0030] When x=Q0, It represents the dynamic threshold value of the inflection point identification parameter of the energy storage system during charging and discharging; Q0 represents the energy curve of the energy storage system during charging and discharging;

[0031] The subscript x may also be equal to other battery parameters associated with the charge and discharge curves.

[0032] Furthermore, the high-value inflection point attribute information is:

[0033] The inflection point attribute information of the battery charge and discharge curve can be restored by relying only on the inflection point attribute information of adjacent inflection points; wherein the deviation between the data of any point on the restored battery charge and discharge curve and the original data does not exceed a deviation threshold.

[0034] Furthermore, the deviation threshold is 2%.

[0035] A dynamic threshold inflection point detection system for energy storage system data, comprising:

[0036] The acquisition module is used to collect battery data and process it to obtain battery parameters; the battery parameters include: battery temperature, charge and discharge current, voltage, and power;

[0037] A calculation module, for obtaining the rate of change of the slope of the charge and discharge curve for each data point based on the charge and discharge current, voltage or power;

[0038] An inflection point determination module is used to determine whether the rate of change of the slope of the charge-discharge curve of each data point meets a first preset condition; if so, the data point is determined to be an inflection point, and information related to the inflection point is saved as inflection point attribute information;

[0039] The target inflection point acquisition module is used to determine whether the inflection point attribute information is high-value inflection point attribute information; if so, save the inflection point attribute information as target inflection point attribute information.

[0040] The beneficial effects of the present invention are:

[0041] 1. By comprehensively considering the battery temperature factor, the inflection point of the battery charge and discharge curve in the energy storage system can be detected more accurately, thereby improving the accuracy of inflection point detection. In addition, the battery charge and discharge curve (voltage or power curve) can be restored with high precision based on the inflection point information alone, and the deviation between any point on the restored curve and the original data does not exceed 2%.

[0042] 2. Setting independent thresholds for different temperature stages makes inflection point detection more consistent with the actual electrochemical characteristics of the battery, enhancing the reliability of the test results.

[0043] 3. Record multi-dimensional information of inflection points, providing rich data support for subsequent system performance analysis and fault diagnosis.

[0044] 4. Filter high-value inflection point information. When the user can accept a certain error range, a large amount of intermediate process information data storage can be deleted, and the inflection point information can be retained. The number of inflection point information records accounts for less than 5% of the original total storage records, which greatly reduces the data processing volume, retains key information, improves retrieval efficiency, and saves hardware resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1This is a flow chart of a method for detecting a dynamic threshold inflection point of energy storage system data according to one embodiment of the present invention;

[0046] Figure 2 This is a flow chart of a method for detecting a dynamic threshold inflection point of energy storage system data according to another embodiment of the present invention;

[0047] Figure 3 Schematic diagram of a dynamic threshold inflection point detection system for energy storage system data according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] The present invention will now be discussed with reference to exemplary embodiments. It should be understood that the embodiments discussed are only intended to enable those skilled in the art to better understand and implement the present invention, rather than to imply any limitation on the scope of the present invention.

[0049] As used herein, the term "including" and variations thereof are to be interpreted as open-ended terms meaning "including, but not limited to." The term "based on" is to be interpreted as "based, at least in part, on." The terms "one embodiment" and "an embodiment" are to be interpreted as "at least one embodiment."

[0050] Example 1

[0051] Figure 1 This is a flow chart of a method for detecting the dynamic threshold inflection point of energy storage system data according to an embodiment of the present invention. Figure 1 As shown, according to one embodiment of the present invention, a method for detecting a dynamic threshold inflection point of energy storage system data includes the following steps:

[0052] Step S102: Collect and process battery data to obtain battery parameters; battery parameters include: battery temperature, charge and discharge current, voltage, and battery capacity;

[0053] Step S104, obtaining the slope change rate of the charge-discharge curve for each data point based on the charge-discharge current, voltage or power;

[0054] Step S106, determining whether the rate of change of the slope of the charge-discharge curve of each data point meets a first preset condition; if so, determining that the data point is an inflection point, and saving information related to the inflection point as inflection point attribute information;

[0055] Step S108 , determining whether the inflection point attribute information is high-value inflection point attribute information; if so, saving the inflection point attribute information as target inflection point attribute information.

[0056] In this embodiment, a method for detecting inflection points based on dynamic threshold values ​​for energy storage system data is proposed. First, key data such as the temperature, charge / discharge current, voltage, and charge level of the battery in the energy storage system is collected in real time. This data is preprocessed, including noise filtering, to obtain accurate battery parameters. Subsequently, the slopes of adjacent time points are calculated based on the charge / discharge curve to obtain the rate of change of the charge / discharge curve slope, which reflects the rate of change of the battery's charge / discharge state. Next, inflection points are identified by determining whether the rate of change of the charge / discharge curve slope for each data point meets a first preset condition, and information related to these inflection points is stored as inflection point attribute information. The first preset condition is that the rate of change of the charge / discharge curve slope for the data point meets the inflection point identification criteria. Various methods exist in the prior art for identifying inflection points based on the curve slope change rate. Any method that can identify a data point as an inflection point can be applied to the present invention. Finally, the value of this inflection point attribute information is further evaluated, and high-value inflection point attribute information is stored as target attribute information, providing important evidence for subsequent performance analysis and optimization of the energy storage system.

[0057] The present invention accurately identifies inflection points by collecting battery data in real time and calculating the rate of change of the slope of the charge and discharge curves, and screens and saves high-value inflection point attribute information, providing an important basis for energy storage system performance analysis and optimization.

[0058] According to one embodiment of the present invention, step S104 includes:

[0059] Step S1042, eliminating abnormal data points in the battery parameters;

[0060] Step S1044, obtaining the real-time slope of the charge-discharge curve for each remaining data point;

[0061] Step S1046 , obtaining a charge-discharge curve slope change rate of each data point based on the real-time slopes of the charge-discharge curves of adjacent data points.

[0062] Preferably, an abnormal data point is: a data point whose value change in adjacent time domains exceeds a jump threshold;

[0063] The jump threshold is p% of the reference value and is set according to actual needs;

[0064] The reference values ​​include: battery rated voltage and battery rated capacity.

[0065] This embodiment further provides a method for obtaining the rate of change of the charge-discharge curve slope for each data point. First, outlier data points in the battery parameters are removed. These outliers are defined as data points whose values ​​change within adjacent time domains by more than a jump threshold p%. The jump threshold is set based on actual needs and, in this embodiment, is specifically set to 2% of a baseline value; the baseline value includes, for example, the rated battery voltage and rated battery capacity. Next, the real-time slope of the charge-discharge curve for each remaining data point is obtained. Finally, based on the real-time slopes of the charge-discharge curves of adjacent data points, the rate of change of the charge-discharge curve slope for each data point is calculated.

[0066] The present invention is based on the characteristics of energy storage batteries, that is, the voltage and power will not experience large jumps. By eliminating large jump points, the accuracy of the data is ensured, thereby providing a reliable basis for subsequent inflection point detection and performance analysis.

[0067] According to one embodiment of the present invention, step S106 includes:

[0068] The discriminant function g is determined by the inflection point of the energy storage data x (V, Q, t, T, μ x ,…) judge the current data point;

[0069]

[0070] Where V is the battery voltage, Q is the battery charge, t is the time, T is the battery temperature, μ x is the slope of the energy storage charge and discharge curve, “…” is other parameters that characterize the energy storage system, μ x ′ is the slope change rate of the energy storage charge and discharge curve; ε x (T) is the slope change rate threshold; x is a battery parameter associated with the charge and discharge curve; T is the battery temperature;

[0071] When g x (V, Q, t, T, μ x , ...) is 1, it means that the data point is an inflection point that meets the slope change rate threshold; when g x (V, Q, t, T, μ x , ...) is 0, indicating that the data point is not an inflection point that meets the slope change rate threshold;

[0072] |μ x ′|≥ε x (T) indicates that the rate of change of the slope of the charge-discharge curve at this data point meets the first preset condition.

[0073] In this embodiment, step S106 judges the current data point by using the energy storage data inflection point discrimination function to determine whether it is an inflection point; this function comprehensively considers the battery voltage, battery power, time, battery temperature and other parameters that characterize the energy storage system, and pays special attention to the slope and change rate of the energy storage charge and discharge curve (i.e., the real-time slope of the charge and discharge curve at each data point and the rate of change of the slope of the charge and discharge curve), and compares the rate of change of the slope of the energy storage charge and discharge curve with a preset slope change rate threshold; when the function g x (V, Q, t, T, μ x , ...) output is 1, indicating that the slope change rate of the data point exceeds the dynamic threshold corresponding to the current temperature stage (i.e., the slope change rate threshold ε x (T)), so the data point is determined to be an inflection point, and the current time, current temperature, and corresponding voltage, power, slope and other multi-dimensional information of the inflection point are recorded as the inflection point attribute information; and when the function g x (V, Q, t, T, μ x , …) When the output result is 0, it means that the data point does not meet the slope change rate threshold condition and is not determined to be an inflection point. Through this method, the key inflection points in the charging and discharging process of the energy storage system can be accurately identified and recorded, providing an important basis for subsequent performance analysis and optimization.

[0074] The present invention accurately identifies and records the key inflection points in the charging and discharging process of the energy storage system through the energy storage data inflection point discriminant function, providing an important basis for subsequent performance analysis and optimization.

[0075] According to one embodiment of the present invention, the slope change rate threshold is:

[0076]

[0077] Among them, ε x (T) is the slope change rate threshold; ε x1 (T) is the first slope change rate threshold; ε x2 (T) is the second slope change rate threshold; ε x3 (T) is the third slope change rate threshold; K1 is the first temperature parameter, K2 is the second temperature parameter, and K1<K2.

[0078] Preferably, the electrochemical characteristics of the battery are obtained based on the material characteristics of the battery, and the first temperature parameter and the second temperature parameter are determined based on the electrochemical characteristics of the battery;

[0079] A first slope change rate threshold, a second slope change rate threshold, and a third slope change rate threshold are determined based on material properties of the battery.

[0080] In this embodiment, the slope change rate threshold is a dynamic threshold, which is divided based on the battery material characteristics and temperature stage. Specifically: First, the electrochemical characteristics are obtained according to the battery material characteristics, and then the first temperature parameter K1 and the second temperature parameter K2 are determined, K1 < K2; the temperature range is divided into three stages: low temperature (T < K1), medium temperature (K1 ≤ T ≤ K2) and high temperature (T > K2), each stage corresponds to a different temperature interval; each interval is further subdivided into stages according to the temperature gradient. Then, the first, second, and third slope change rate thresholds are determined respectively according to the battery material characteristics, and an independent slope change rate threshold is assigned to each temperature stage as an inflection point identification parameter, where the low temperature stage threshold is the first slope change rate threshold ε x1 (T), the high temperature stage threshold is the third slope change rate threshold ε x3 (T), the medium temperature stage threshold is the second slope change rate threshold ε x2 (T); the slope change rate thresholds corresponding to each temperature stage are determined according to a certain relationship based on the specific battery material characteristics. These three slope change rate thresholds may exhibit a constant, a linear relationship, or a nonlinear relationship with the battery temperature T for different battery materials. Finally, for the charge and discharge curves within each temperature stage, the slopes of the charge and discharge curves at adjacent time points are calculated to facilitate subsequent inflection point detection and analysis. This method can more accurately identify the charge and discharge inflection points of the energy storage system under different temperature conditions, providing strong support for performance evaluation and optimization.

[0081] By setting a dynamic slope change rate threshold based on battery material characteristics and temperature stage divisions, the present invention can more accurately identify the charging and discharging inflection points of the energy storage system under different temperature conditions, providing strong support for performance evaluation and optimization.

[0082] According to one embodiment of the present invention, when x=V0, Represents the dynamic threshold value of the voltage inflection point identification parameter during the charging and discharging of the energy storage system; V0 represents the voltage curve during the charging and discharging of the energy storage system;

[0083] When x=Q0, It represents the dynamic threshold value of the inflection point identification parameter of the energy storage system during charging and discharging; Q0 represents the energy curve of the energy storage system during charging and discharging;

[0084] The subscript x may also be equal to other battery parameters associated with the charge and discharge curves.

[0085] In this embodiment, the concept of dynamic threshold is introduced for the inflection point identification during the charging and discharging process of the energy storage system. Specifically, when the lower subscript x is set to V0 (representing the voltage curve during the charging and discharging of the energy storage system), the corresponding dynamic threshold It is the dynamic threshold value of the voltage inflection point identification parameter when the energy storage system is charging and discharging, which is used to determine the inflection point on the voltage curve; similarly, when the subscript x is set to Q0 (representing the charge curve when the energy storage system is charging and discharging), the corresponding dynamic threshold value is It is the dynamic threshold of the inflection point identification parameter of the energy storage system during charging and discharging, which is used to determine the inflection point on the energy curve. In addition, the value of the subscript x is not limited to V0 or Q0. It can also be equal to other battery parameters that are associated with the charge and discharge curve, such as temperature, current, etc. As long as these parameters can affect the changes in the charge and discharge curve, the corresponding dynamic threshold can be set as the inflection point identification parameter, so as to more comprehensively identify the various inflection points in the charge and discharge process of the energy storage system and provide richer information for the performance analysis and optimization of the system.

[0086] By introducing the concept of dynamic thresholds, the present invention sets corresponding inflection point identification parameters for different parameters (such as voltage and power) in the charging and discharging process of the energy storage system. This can more comprehensively and accurately identify various inflection points in the charging and discharging process, providing rich information for system performance analysis and optimization.

[0087] According to one embodiment of the present invention, the high-value inflection point attribute information in step S108 is:

[0088] The inflection point attribute information of the battery charge and discharge curve can be restored by relying only on the inflection point attribute information of adjacent inflection points; wherein the deviation between the data of any point on the restored battery charge and discharge curve and the original data does not exceed a deviation threshold.

[0089] Preferably, the deviation threshold is 2%.

[0090] In this embodiment, the high-value inflection point attribute information in step S108 is specifically: the original battery charge and discharge curve can be highly restored only by the attribute information of adjacent inflection points (covering the temperature stage, current time, battery temperature, voltage, power, slope, etc.), and the deviation between the restored curve and the original data at any point does not exceed the preset deviation threshold. The deviation threshold is set according to actual needs. In this embodiment, it is preferably 2%, which means that the high-value inflection point information contains rich curve characteristics. Without additional data assistance, based only on the attribute information of these inflection points, a curve that is highly consistent with the original charge and discharge curve can be reproduced through mathematical methods such as interpolation and fitting, which not only achieves data simplification but also ensures the integrity of key information, providing reliable and efficient data support for subsequent system performance analysis.

[0091] By screening high-value inflection point attribute information, the present invention can highly restore the original battery charge and discharge curve with minimal deviation by using only the attribute information of adjacent inflection points, achieving a balance between data simplification and key information integrity, and providing reliable and efficient data support for system performance analysis.

[0092] Example 2

[0093] Figure 2 This is a flow chart of a method for detecting the dynamic threshold inflection point of energy storage system data in another embodiment of the present invention. Figure 2 As shown, according to one embodiment of the present invention, a method for detecting a dynamic threshold inflection point of energy storage system data includes the following steps:

[0094] Step S201, data collection and preprocessing;

[0095] A sensor suite is installed on the energy storage system's battery pack to measure the battery status. The suite includes high-precision temperature, current, voltage, and power sensors. A data processing unit is designed to filter the collected data for noise, including the use of a low-pass filtering algorithm to remove noise interference.

[0096] The installed sensor group collects real-time data on the battery temperature, charge and discharge current, voltage, and power in the energy storage system. The data processing unit performs noise filtering to ensure the accuracy and reliability of the data.

[0097] Step S202, temperature stage division;

[0098] Obtaining the material properties of the battery, and obtaining the electrochemical properties of the battery based on the material properties of the battery, and determining the battery temperature parameters based on the electrochemical properties of the battery, including: a first temperature parameter K1 and a second temperature parameter K2, K1 < K2, and dividing the temperature interval by the battery temperature parameters, including:

[0099] Low temperature range: T<K1;

[0100] Medium temperature range: K1≤T≤K2;

[0101] High temperature range: T>K2;

[0102] Where T is the battery temperature.

[0103] Within each temperature range, the temperature gradient is further subdivided into multiple sub-stages. For example, a 3°C temperature gradient is used, with each sub-stage divided every 3°C. Based on the battery temperature range, the temperature is divided into three consecutive temperature stages: low temperature, medium temperature, and high temperature, each corresponding to a different temperature range.

[0104] Step S203, slope change rate calculation

[0105] A slope calculation algorithm is developed in the data processing unit to calculate the real-time slope of the charge and discharge curve based on the collected time series data. At the same time, judgment logic is set to identify and eliminate significant jump points in the voltage and power data. The criterion for determining a significant jump point is that the value exceeds the reference value (rated voltage, rated power) by p%, for example, p% = 2%.

[0106] Based on the inherent characteristics of the energy storage battery, where significant jumps in voltage and charge are unlikely, significant jumps are eliminated. For the charge and discharge curve within each temperature stage, the slope of the charge and discharge curve at adjacent time points at time t is calculated. This calculation method includes calculating the real-time slope of the charge and discharge voltage curve.

[0107] Step S204, dynamic threshold setting;

[0108] In different temperature ranges, the corresponding slope change rate thresholds are determined through experimental testing and data analysis, including: the first slope change rate threshold ε x1 (T), the second slope change rate threshold ε x2 (T), the third slope change rate threshold ε x3 A mapping relationship between the slope change rate threshold and temperature is established. Based on the real-time collected battery temperature T, a table is used to obtain the slope change rate threshold corresponding to the current temperature stage.

[0109] Assign a corresponding slope change rate threshold to each temperature stage,

[0110] In the low temperature stage, the first slope change rate threshold is ε x1 (T);

[0111] In the medium temperature stage, the second slope change rate threshold is ε x2 (T);

[0112] In the high temperature stage, the third slope change rate threshold is ε x3 (T);

[0113] Among them, the slope change rate threshold ε x1 (T),ε x2 (T) and ε x3 The size relationship of (T) varies depending on different battery materials, where T is the battery temperature.

[0114] According to the current temperature stage, determine the slope change rate threshold ε x (T):

[0115]

[0116] ε x1 (T)=A x (T)

[0117] ε x2 (T)=B x (T)

[0118] ε x3 (T)=C x (T)

[0119] Wherein, x is the battery parameter associated with the charge and discharge curve; A x (T), B x (T), C x (T) are the first coefficient, the second coefficient, and the third coefficient respectively;

[0120] V0 represents the voltage curve of the energy storage system during charging and discharging. When x=V0, It represents the dynamic threshold value of the voltage inflection point identification parameter when the energy storage system is charging and discharging; Q0 represents the charge curve when the energy storage system is charging and discharging. When x=Q0, Represents the dynamic threshold value of the energy storage system's charge and discharge inflection point identification parameter; the subscript x can also be equal to other battery parameters, as long as the battery parameters are correlated with the charge and discharge curves;

[0121] The first coefficient, the second coefficient, and the third coefficient are determined by the material properties of the energy storage battery and can be constants or have a linear or nonlinear relationship with the battery temperature T;

[0122] Step S205, inflection point identification and marking;

[0123] Inflection point identification logic is integrated into the data processing unit to compare the slope change rate of the battery voltage / capacity with the slope change rate threshold corresponding to the current temperature stage in real time. When the slope change rate of the real-time battery voltage / capacity exceeds the slope change rate threshold corresponding to the current temperature stage, the inflection point identification mechanism is triggered, the point is determined to be an inflection point, and the inflection point attribute information is recorded. The inflection point attribute information is a multi-dimensional information including: the temperature stage, time, battery temperature, voltage, capacity, slope, and other information. This multi-dimensional information is recorded in detail as the inflection point attribute information.

[0124] The discriminant function g is determined by the inflection point of the energy storage data x (V, Q, t, T, μ x ,…) to judge the inflection point;

[0125]

[0126] Where V is the battery voltage, Q is the battery charge, t is the time, T is the battery temperature, μ x is the slope of the energy storage charge and discharge curve, “…” is other parameters that characterize the energy storage system, μ x ′ is the slope change rate of the energy storage charge and discharge curve;

[0127] When x=V0, V0 represents the voltage curve of the energy storage system during charging and discharging. Indicates the slope of the voltage curve of the energy storage system at time t; when x = Q0, Q0 represents the charge curve of the energy storage system during charging and discharging. It represents the slope of the energy storage system's charge curve at time t. The subscript x can also be equal to other battery parameters, as long as the battery parameters are correlated with the charge and discharge curves.

[0128] When g x (V, Q, t, T, μ x , ...) is 1, indicating that the data point satisfies the dynamic threshold (such as ) inflection point, and save the information related to the data point as inflection point attribute information; when g x (V, Q, t, T, μ x , ...) is 0, indicating that the data point is not an inflection point that satisfies the dynamic threshold, and the information related to the data point is not saved.

[0129] Step S206, screening high-value density information;

[0130] After completing inflection point detection, the designed screening algorithm is used to analyze the recorded inflection point attribute information, combined with the battery temperature and voltage parameters before and after the inflection point. Based on preset conditions, high-value inflection point attribute information is obtained as target inflection point attribute information. This target inflection point attribute information is saved and used for subsequent system performance analysis, as the target inflection point attribute information has higher value for system performance analysis.

[0131] High-value inflection point attribute information is: the inflection point attribute information of the battery charge and discharge curve (voltage or power curve) can be restored by relying only on the inflection point attribute information of adjacent inflection points without relying on other information; wherein the deviation between the data at any point on the restored battery charge and discharge curve and the original data does not exceed a deviation threshold d%, for example, d% = 2%.

[0132] This invention achieves precise detection of dynamic threshold inflection points in energy storage system data based on battery temperature characteristics. Through multi-stage temperature division and dynamic threshold adaptation, the accuracy of inflection point identification is effectively improved, and high-precision restoration of charge and discharge curves (voltage / capacity) (deviation ≤ 2%) can be achieved based solely on high-value inflection point information. In applications that meet precision requirements, this can significantly reduce data storage size, optimize data retrieval efficiency, and significantly reduce hardware resource usage.

[0133] Example 3

[0134] Figure 3 This is a schematic diagram of a dynamic threshold inflection point detection system for energy storage system data according to an embodiment of the present invention. Figure 3As shown, according to one embodiment of the present invention, a dynamic threshold inflection point detection system for energy storage system data includes:

[0135] The acquisition module 10 is used to collect battery data and process it to obtain battery parameters; the battery parameters include: battery temperature, charge and discharge current, voltage, and power;

[0136] A calculation module 20 is used to obtain the rate of change of the slope of the charge and discharge curve for each data point based on the charge and discharge current, voltage or power;

[0137] An inflection point determination module 30 is configured to determine whether the rate of change of the slope of the charge-discharge curve of each data point satisfies a first preset condition; if so, the data point is determined to be an inflection point, and information related to the inflection point is stored as inflection point attribute information;

[0138] The target inflection point acquisition module 40 is configured to determine whether the inflection point attribute information is high-value inflection point attribute information; if so, save the inflection point attribute information as target inflection point attribute information.

[0139] In this embodiment, a dynamic threshold inflection point detection system for energy storage system data is proposed, which includes four core modules to achieve key inflection point identification and high-value information screening during the battery charging and discharging process: First, the acquisition module 10 is responsible for collecting battery data (such as battery temperature, charge and discharge current, voltage, and power), and preprocessing it to obtain various parameters reflecting the battery operating status. Second, the calculation module 20 calculates the slope change rate of the charge and discharge curve corresponding to each data point based on these parameters to quantify the dynamic changes in the curve shape. Subsequently, the inflection point judgment module 30 judges each data point based on a first preset condition (such as whether the slope change rate exceeds a threshold). If the condition is met, it is marked as an inflection point and its related attribute information (such as time, temperature, voltage, power, slope, etc.) is saved. Finally, the target inflection point acquisition module 40 further evaluates whether the attribute information of the identified inflection point meets the high-value standard (such as whether the original charge and discharge curve can be highly restored with minimal deviation based solely on the adjacent inflection point information). If so, it is saved as the target inflection point attribute information, thereby ensuring data streamlining while providing accurate and efficient data support for subsequent battery performance analysis.

[0140] The present invention realizes the accurate identification of key inflection points and the screening of high-value information during the battery charging and discharging process, and provides accurate and efficient data support for battery performance analysis while ensuring data simplification.

[0141] Those skilled in the art will clearly understand that, for the convenience and brevity of description, the specific working process of the system described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0142] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention herein is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features having similar functions disclosed in this application.

[0143] It should be understood that the size of the serial numbers of each step in the content of the invention and the embodiments of the present invention does not absolutely mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

Claims

1. A method for detecting a dynamic threshold inflection point of energy storage system data, characterized in that: The method comprises: Collect and process battery data to obtain battery parameters; the battery parameters include: battery temperature, charge and discharge current, voltage, and power; Based on the charge and discharge current, voltage or power, obtain the rate of change of the charge and discharge curve slope for each data point; Determine whether the rate of change of the slope of the charge-discharge curve of each data point meets a first preset condition; if so, determine that the data point is an inflection point, and save information related to the inflection point as inflection point attribute information; Determine whether the inflection point attribute information is high-value inflection point attribute information; if so, save the inflection point attribute information as target inflection point attribute information.

2. The method for detecting the dynamic threshold inflection point of energy storage system data according to claim 1, characterized in that: Obtain the rate of change of the charge and discharge curve slope for each data point, including: Eliminating abnormal data points in the battery parameters; Obtain the real-time slope of the charge and discharge curve for each remaining data point; The rate of change of the charge-discharge curve slope of each data point is obtained based on the real-time slope of the charge-discharge curve of adjacent data points.

3. The method for detecting the dynamic threshold inflection point of energy storage system data according to claim 2, characterized in that: The abnormal data point is: the change in the value of the data point in the adjacent time domain exceeds the jump threshold; The jump threshold is p% of the reference value and is set according to actual needs; The reference values ​​include: battery rated voltage and battery rated capacity.

4. The method for detecting the dynamic threshold inflection point of energy storage system data according to claim 1, characterized in that: Determining whether the rate of change of the slope of the charge-discharge curve of each data point meets a first preset condition includes: The discriminant function g is determined by the inflection point of the energy storage data x (V, Q, t, T, μ x ,…) judge the current data point; Where V is the battery voltage, Q is the battery charge, t is the time, T is the battery temperature, μ x is the slope of the energy storage charge and discharge curve, "..." is other parameters that characterize the energy storage system, μ x ′ is the slope change rate of the energy storage charge and discharge curve; ε x (T) is the slope change rate threshold; x is a battery parameter associated with the charge and discharge curve; T is the battery temperature; When g x (V, Q, t, T, μ x , ...) is 1, it means that the data point is an inflection point that meets the slope change rate threshold; when g x (V, Q, t, T, μ x , ...) is 0, indicating that the data point is not an inflection point that meets the slope change rate threshold; |μ x ′|≥ε x (T) indicates that the rate of change of the slope of the charge-discharge curve at this data point meets the first preset condition.

5. The method for detecting the dynamic threshold inflection point of energy storage system data according to claim 4, characterized in that: The slope change rate threshold is: Among them, ε x (T) is the slope change rate threshold; ε x1 (T) is the first slope change rate threshold; ε x2 (T) is the second slope change rate threshold; ε x3 (T) is the third slope change rate threshold; K1 is the first temperature parameter, K2 is the second temperature parameter, and K1<K2.

6. The method for detecting the dynamic threshold inflection point of energy storage system data according to claim 5, characterized in that: obtaining electrochemical characteristics of the battery based on material characteristics of the battery, and determining a first temperature parameter and a second temperature parameter based on the electrochemical characteristics of the battery; A first slope change rate threshold, a second slope change rate threshold, and a third slope change rate threshold are determined based on material properties of the battery.

7. The method for detecting the dynamic threshold inflection point of energy storage system data according to claim 4, characterized in that: When x=V0, Represents the dynamic threshold value of the voltage inflection point identification parameter during the charging and discharging of the energy storage system; V0 represents the voltage curve during the charging and discharging of the energy storage system; When x=Q0, It represents the dynamic threshold value of the inflection point identification parameter of the energy storage system during charging and discharging; Q0 represents the energy curve of the energy storage system during charging and discharging; The subscript x may also be equal to other battery parameters associated with the charge and discharge curves.

8. The method for detecting the dynamic threshold inflection point of energy storage system data according to claim 1, characterized in that: The high-value inflection point attribute information is: The inflection point attribute information of the battery charge and discharge curve can be restored by relying only on the inflection point attribute information of adjacent inflection points; wherein the deviation between the data of any point on the restored battery charge and discharge curve and the original data does not exceed a deviation threshold.

9. The method for detecting the dynamic threshold inflection point of energy storage system data according to claim 8, characterized in that: The deviation threshold is 2%.

10. A dynamic threshold inflection point detection system for energy storage system data, characterized in that: The detection system comprises: The acquisition module is used to collect battery data and process it to obtain battery parameters; the battery parameters include: battery temperature, charge and discharge current, voltage, and power; A calculation module, for obtaining the rate of change of the slope of the charge and discharge curve for each data point based on the charge and discharge current, voltage or power; An inflection point determination module is used to determine whether the rate of change of the slope of the charge-discharge curve of each data point meets a first preset condition; if so, the data point is determined to be an inflection point, and information related to the inflection point is saved as inflection point attribute information; The target inflection point acquisition module is used to determine whether the inflection point attribute information is high-value inflection point attribute information; if so, save the inflection point attribute information as target inflection point attribute information.

Images